本文整理汇总了Python中constants.Constants.get_indices方法的典型用法代码示例。如果您正苦于以下问题：Python Constants.get_indices方法的具体用法？Python Constants.get_indices怎么用？Python Constants.get_indices使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类constants.Constants的用法示例。
在下文中一共展示了Constants.get_indices方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: __init__
# 需要导入模块: from constants import Constants [as 别名]
# 或者: from constants.Constants import get_indices [as 别名]
#.........这里部分代码省略.........
[[coder[self.tri, self.left, s, t]]],
labels= label_indices)
label_indices = self.compute_label_indices(self.tri,
self.right, s, t)
chart.set_t(coder[self.tri, self.right, s, t],
coder[self.trap, self.right, s, s+1:t+1],
coder[self.tri_stop, self.right, s+1:t+1, t])
if s!=0 or (s==0 and t==n-1):
label_indices = self.compute_label_indices(self.tri_stop,
self.right, s, t)
chart.set(coder[self.tri_stop, self.right, s, t],
[[coder[self.tri, self.right, s, t]]],
labels=label_indices)
self.graph = chart.finish()
return self.graph
def compute_weights(self, label_scores):
if self.weights == None:
self.weights = pydecode.transform(self.graph, label_scores)
return self.weights
def reset_values(self):
self.weights = None
def compute_marginals(self, label_scores):
self.compute_weights(label_scores)
edge_marginals = pydecode.marginals(self.graph, self.weights)
return edge_marginals
def best_path(self, label_scores):
self.compute_weights(label_scores)
return pydecode.best_path(self.graph, self.weights)
def best_edges(self, label_scores):
path = self.best_path(label_scores)
best_edges = path.edges
heads = np.array([], dtype=np.int64)
for edge in best_edges:
heads = np.append(heads, edge.head.label)
shapes, direction, head, modifier = self.get_indices_of_heads(heads,
len(self.sentence))
print "shapes"
pprint.pprint(shapes)
print "direct"
pprint.pprint(direction)
print "head"
pprint.pprint(head)
print "mod"
pprint.pprint(modifier)
right_indices = np.where(direction == 0)
left_indices = np.where(direction == 1)
depen = np.full(len(self.sentence), -1, dtype=np.int64)
depen[modifier[right_indices].tolist()] = head[right_indices].tolist()
depen[head[left_indices].tolist()] = modifier[left_indices].tolist()
return depen
def get_indices_of_heads(self, heads, n):
shapes, direction, row, column = self.constants.get_indices(heads, n)
indices_needed = np.where(shapes == 1)
return shapes[indices_needed], direction[indices_needed], row[indices_needed], column[indices_needed]
def compute_label_indices(self, shape, direction, head, mod):
indices = np.tile([shape, direction, 0, head, mod], abs(head-mod)).\
reshape(abs(head-mod), 5)
indices[:,2] = self.compute_adj(head, mod)
if(indices.shape[0] == 1):
return np.array([self.out[indices[0,0], indices[0,1], indices[0,2],
indices[0, 3], indices[0, 4]]])
return self.out[indices[:,0].tolist(),indices[:,1].tolist(),
indices[:,2].tolist(), indices[:,3].tolist(), indices[:,4].tolist()]
def compute_adj(self, head, mod):
if(head > mod):
split = np.arange(mod, head)
else:
split = np.arange(head, mod)
vfunc = np.vectorize(self.is_adj)
return vfunc(head, split)
def is_adj(self, head, split):
if abs(head - split) <=1:
return self.adj
else:
return self.non_adj